Overview

Brought to you by YData

Dataset statistics

Number of variables24
Number of observations708
Missing cells4556
Missing cells (%)26.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory1.5 KiB

Variable types

Numeric8
URL3
Text4
Categorical4
Unsupported3
DateTime2

Alerts

averageRuntime is highly overall correlated with runtimeHigh correlation
externals_thetvdb is highly overall correlated with externals_tvrage and 1 other fieldsHigh correlation
externals_tvrage is highly overall correlated with externals_thetvdbHigh correlation
id is highly overall correlated with externals_thetvdb and 1 other fieldsHigh correlation
runtime is highly overall correlated with averageRuntimeHigh correlation
weight is highly overall correlated with idHigh correlation
schedule_time is highly imbalanced (58.2%) Imbalance
language has 45 (6.4%) missing values Missing
genres has 253 (35.7%) missing values Missing
runtime has 555 (78.4%) missing values Missing
averageRuntime has 57 (8.1%) missing values Missing
ended has 531 (75.0%) missing values Missing
officialSite has 80 (11.3%) missing values Missing
schedule_days has 217 (30.6%) missing values Missing
rating has 582 (82.2%) missing values Missing
summary has 96 (13.6%) missing values Missing
webChannel_name has 20 (2.8%) missing values Missing
webChannel_site has 188 (26.6%) missing values Missing
dvd_country has 705 (99.6%) missing values Missing
externals_tvrage has 685 (96.8%) missing values Missing
externals_thetvdb has 198 (28.0%) missing values Missing
externals_imdb has 344 (48.6%) missing values Missing
id has unique values Unique
url has unique values Unique
updated has unique values Unique
genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
schedule_days is an unsupported type, check if it needs cleaning or further analysis Unsupported
dvd_country is an unsupported type, check if it needs cleaning or further analysis Unsupported
weight has 12 (1.7%) zeros Zeros

Reproduction

Analysis started2025-02-10 19:27:29.353649
Analysis finished2025-02-10 19:27:42.781568
Duration13.43 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

id
Real number (ℝ)

High correlation  Unique 

Distinct708
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61329.328
Minimum274
Maximum82453
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:42.922005image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum274
5-th percentile11697.3
Q154985.5
median69427.5
Q373898.5
95-th percentile78146.3
Maximum82453
Range82179
Interquartile range (IQR)18913

Descriptive statistics

Standard deviation19377.282
Coefficient of variation (CV)0.31595457
Kurtosis2.0106714
Mean61329.328
Median Absolute Deviation (MAD)5995.5
Skewness-1.6536618
Sum43421164
Variance3.7547904 × 108
MonotonicityNot monotonic
2025-02-10T14:27:43.081136image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51908 1
 
0.1%
74082 1
 
0.1%
66342 1
 
0.1%
26350 1
 
0.1%
76058 1
 
0.1%
58177 1
 
0.1%
74141 1
 
0.1%
6141 1
 
0.1%
55986 1
 
0.1%
57945 1
 
0.1%
Other values (698) 698
98.6%
ValueCountFrequency (%)
274 1
0.1%
703 1
0.1%
718 1
0.1%
729 1
0.1%
793 1
0.1%
802 1
0.1%
812 1
0.1%
875 1
0.1%
920 1
0.1%
938 1
0.1%
ValueCountFrequency (%)
82453 1
0.1%
82397 1
0.1%
82316 1
0.1%
82298 1
0.1%
81933 1
0.1%
81893 1
0.1%
81775 1
0.1%
81758 1
0.1%
81749 1
0.1%
81561 1
0.1%

url
URL

Unique 

Distinct708
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size75.5 KiB
https://www.tvmaze.com/shows/51908/neznost
 
1
https://www.tvmaze.com/shows/74082/girls-play
 
1
https://www.tvmaze.com/shows/66342/carina-bergfeldt
 
1
https://www.tvmaze.com/shows/26350/nytt-pa-nytt
 
1
https://www.tvmaze.com/shows/76058/the-uplift
 
1
Other values (703)
703 
ValueCountFrequency (%)
https://www.tvmaze.com/shows/51908/neznost 1
 
0.1%
https://www.tvmaze.com/shows/74082/girls-play 1
 
0.1%
https://www.tvmaze.com/shows/66342/carina-bergfeldt 1
 
0.1%
https://www.tvmaze.com/shows/26350/nytt-pa-nytt 1
 
0.1%
https://www.tvmaze.com/shows/76058/the-uplift 1
 
0.1%
https://www.tvmaze.com/shows/58177/the-traitors 1
 
0.1%
https://www.tvmaze.com/shows/74141/wang-zhe-rongyao 1
 
0.1%
https://www.tvmaze.com/shows/6141/simons-cat 1
 
0.1%
https://www.tvmaze.com/shows/55986/journey-across-japan 1
 
0.1%
https://www.tvmaze.com/shows/57945/i-like-to-watch 1
 
0.1%
Other values (698) 698
98.6%
ValueCountFrequency (%)
https 708
100.0%
ValueCountFrequency (%)
www.tvmaze.com 708
100.0%
ValueCountFrequency (%)
/shows/51908/neznost 1
 
0.1%
/shows/74082/girls-play 1
 
0.1%
/shows/66342/carina-bergfeldt 1
 
0.1%
/shows/26350/nytt-pa-nytt 1
 
0.1%
/shows/76058/the-uplift 1
 
0.1%
/shows/58177/the-traitors 1
 
0.1%
/shows/74141/wang-zhe-rongyao 1
 
0.1%
/shows/6141/simons-cat 1
 
0.1%
/shows/55986/journey-across-japan 1
 
0.1%
/shows/57945/i-like-to-watch 1
 
0.1%
Other values (698) 698
98.6%
ValueCountFrequency (%)
708
100.0%
ValueCountFrequency (%)
708
100.0%

name
Text

Distinct706
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size58.7 KiB
2025-02-10T14:27:43.340930image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Length

Max length63
Median length40
Mean length17.326271
Min length2

Characters and Unicode

Total characters12267
Distinct characters167
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique704 ?
Unique (%)99.4%

Sample

1st rowНежность
2nd rowПредпоследняя инстанция
3rd rowМанюня
4th rowНедетское кино
5th rowУспешный
ValueCountFrequency (%)
the 111
 
5.2%
of 39
 
1.8%
with 21
 
1.0%
a 20
 
0.9%
18
 
0.8%
love 15
 
0.7%
and 15
 
0.7%
in 12
 
0.6%
you 12
 
0.6%
no 11
 
0.5%
Other values (1438) 1868
87.2%
2025-02-10T14:27:43.788191image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1434
 
11.7%
e 1066
 
8.7%
a 727
 
5.9%
n 634
 
5.2%
o 630
 
5.1%
i 612
 
5.0%
r 560
 
4.6%
t 505
 
4.1%
s 460
 
3.7%
h 352
 
2.9%
Other values (157) 5287
43.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12267
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1434
 
11.7%
e 1066
 
8.7%
a 727
 
5.9%
n 634
 
5.2%
o 630
 
5.1%
i 612
 
5.0%
r 560
 
4.6%
t 505
 
4.1%
s 460
 
3.7%
h 352
 
2.9%
Other values (157) 5287
43.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12267
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1434
 
11.7%
e 1066
 
8.7%
a 727
 
5.9%
n 634
 
5.2%
o 630
 
5.1%
i 612
 
5.0%
r 560
 
4.6%
t 505
 
4.1%
s 460
 
3.7%
h 352
 
2.9%
Other values (157) 5287
43.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12267
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1434
 
11.7%
e 1066
 
8.7%
a 727
 
5.9%
n 634
 
5.2%
o 630
 
5.1%
i 612
 
5.0%
r 560
 
4.6%
t 505
 
4.1%
s 460
 
3.7%
h 352
 
2.9%
Other values (157) 5287
43.1%

type
Categorical

Distinct11
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
Scripted
229 
Animation
117 
Documentary
90 
Reality
90 
Talk Show
80 
Other values (6)
102 

Length

Max length11
Median length10
Mean length8.3206215
Min length4

Characters and Unicode

Total characters5891
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowScripted
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted 229
32.3%
Animation 117
16.5%
Documentary 90
 
12.7%
Reality 90
 
12.7%
Talk Show 80
 
11.3%
News 38
 
5.4%
Game Show 32
 
4.5%
Variety 14
 
2.0%
Sports 13
 
1.8%
Panel Show 4
 
0.6%

Length

2025-02-10T14:27:43.952411image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scripted 229
27.8%
animation 117
14.2%
show 117
14.2%
documentary 90
 
10.9%
reality 90
 
10.9%
talk 80
 
9.7%
news 38
 
4.6%
game 32
 
3.9%
variety 14
 
1.7%
sports 13
 
1.6%
Other values (2) 5
 
0.6%

Most occurring characters

ValueCountFrequency (%)
i 567
 
9.6%
t 553
 
9.4%
e 497
 
8.4%
a 428
 
7.3%
S 359
 
6.1%
r 347
 
5.9%
o 337
 
5.7%
n 328
 
5.6%
c 319
 
5.4%
p 242
 
4.1%
Other values (18) 1914
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5891
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 567
 
9.6%
t 553
 
9.4%
e 497
 
8.4%
a 428
 
7.3%
S 359
 
6.1%
r 347
 
5.9%
o 337
 
5.7%
n 328
 
5.6%
c 319
 
5.4%
p 242
 
4.1%
Other values (18) 1914
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5891
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 567
 
9.6%
t 553
 
9.4%
e 497
 
8.4%
a 428
 
7.3%
S 359
 
6.1%
r 347
 
5.9%
o 337
 
5.7%
n 328
 
5.6%
c 319
 
5.4%
p 242
 
4.1%
Other values (18) 1914
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5891
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 567
 
9.6%
t 553
 
9.4%
e 497
 
8.4%
a 428
 
7.3%
S 359
 
6.1%
r 347
 
5.9%
o 337
 
5.7%
n 328
 
5.6%
c 319
 
5.4%
p 242
 
4.1%
Other values (18) 1914
32.5%

language
Categorical

Missing 

Distinct33
Distinct (%)5.0%
Missing45
Missing (%)6.4%
Memory size44.0 KiB
English
274 
Chinese
117 
Russian
64 
Norwegian
31 
Swedish
 
23
Other values (28)
154 

Length

Max length10
Median length7
Mean length6.984917
Min length4

Characters and Unicode

Total characters4631
Distinct characters42
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)1.5%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowEnglish

Common Values

ValueCountFrequency (%)
English 274
38.7%
Chinese 117
16.5%
Russian 64
 
9.0%
Norwegian 31
 
4.4%
Swedish 23
 
3.2%
Korean 22
 
3.1%
Japanese 15
 
2.1%
Spanish 12
 
1.7%
French 11
 
1.6%
Thai 10
 
1.4%
Other values (23) 84
 
11.9%
(Missing) 45
 
6.4%

Length

2025-02-10T14:27:44.119321image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english 274
41.3%
chinese 117
17.6%
russian 64
 
9.7%
norwegian 31
 
4.7%
swedish 23
 
3.5%
korean 22
 
3.3%
japanese 15
 
2.3%
spanish 12
 
1.8%
french 11
 
1.7%
thai 10
 
1.5%
Other values (23) 84
 
12.7%

Most occurring characters

ValueCountFrequency (%)
i 610
13.2%
n 609
13.2%
s 598
12.9%
h 480
10.4%
e 374
8.1%
g 311
6.7%
l 287
 
6.2%
E 274
 
5.9%
a 236
 
5.1%
C 119
 
2.6%
Other values (32) 733
15.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4631
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 610
13.2%
n 609
13.2%
s 598
12.9%
h 480
10.4%
e 374
8.1%
g 311
6.7%
l 287
 
6.2%
E 274
 
5.9%
a 236
 
5.1%
C 119
 
2.6%
Other values (32) 733
15.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4631
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 610
13.2%
n 609
13.2%
s 598
12.9%
h 480
10.4%
e 374
8.1%
g 311
6.7%
l 287
 
6.2%
E 274
 
5.9%
a 236
 
5.1%
C 119
 
2.6%
Other values (32) 733
15.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4631
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 610
13.2%
n 609
13.2%
s 598
12.9%
h 480
10.4%
e 374
8.1%
g 311
6.7%
l 287
 
6.2%
E 274
 
5.9%
a 236
 
5.1%
C 119
 
2.6%
Other values (32) 733
15.8%

genres
Unsupported

Missing  Rejected  Unsupported 

Missing253
Missing (%)35.7%
Memory size50.7 KiB

status
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size44.9 KiB
Running
436 
Ended
177 
To Be Determined
95 

Length

Max length16
Median length7
Mean length7.7076271
Min length5

Characters and Unicode

Total characters5457
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running 436
61.6%
Ended 177
25.0%
To Be Determined 95
 
13.4%

Length

2025-02-10T14:27:44.254879image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-10T14:27:44.421778image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
ValueCountFrequency (%)
running 436
48.6%
ended 177
19.7%
to 95
 
10.6%
be 95
 
10.6%
determined 95
 
10.6%

Most occurring characters

ValueCountFrequency (%)
n 1580
29.0%
e 557
 
10.2%
i 531
 
9.7%
d 449
 
8.2%
R 436
 
8.0%
u 436
 
8.0%
g 436
 
8.0%
190
 
3.5%
E 177
 
3.2%
T 95
 
1.7%
Other values (6) 570
 
10.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5457
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1580
29.0%
e 557
 
10.2%
i 531
 
9.7%
d 449
 
8.2%
R 436
 
8.0%
u 436
 
8.0%
g 436
 
8.0%
190
 
3.5%
E 177
 
3.2%
T 95
 
1.7%
Other values (6) 570
 
10.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5457
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1580
29.0%
e 557
 
10.2%
i 531
 
9.7%
d 449
 
8.2%
R 436
 
8.0%
u 436
 
8.0%
g 436
 
8.0%
190
 
3.5%
E 177
 
3.2%
T 95
 
1.7%
Other values (6) 570
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5457
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1580
29.0%
e 557
 
10.2%
i 531
 
9.7%
d 449
 
8.2%
R 436
 
8.0%
u 436
 
8.0%
g 436
 
8.0%
190
 
3.5%
E 177
 
3.2%
T 95
 
1.7%
Other values (6) 570
 
10.4%

runtime
Real number (ℝ)

High correlation  Missing 

Distinct46
Distinct (%)30.1%
Missing555
Missing (%)78.4%
Infinite0
Infinite (%)0.0%
Mean46.398693
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:44.592045image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q119
median30
Q360
95-th percentile132
Maximum300
Range299
Interquartile range (IQR)41

Descriptive statistics

Standard deviation46.832054
Coefficient of variation (CV)1.00934
Kurtosis8.0695349
Mean46.398693
Median Absolute Deviation (MAD)19
Skewness2.5142541
Sum7099
Variance2193.2413
MonotonicityNot monotonic
2025-02-10T14:27:44.756309image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
60 25
 
3.5%
30 20
 
2.8%
20 8
 
1.1%
120 8
 
1.1%
24 6
 
0.8%
10 6
 
0.8%
25 6
 
0.8%
5 6
 
0.8%
45 6
 
0.8%
12 5
 
0.7%
Other values (36) 57
 
8.1%
(Missing) 555
78.4%
ValueCountFrequency (%)
1 1
 
0.1%
2 2
 
0.3%
3 1
 
0.1%
4 1
 
0.1%
5 6
0.8%
6 1
 
0.1%
7 1
 
0.1%
8 3
0.4%
10 6
0.8%
11 3
0.4%
ValueCountFrequency (%)
300 1
 
0.1%
240 1
 
0.1%
210 1
 
0.1%
180 3
 
0.4%
159 1
 
0.1%
150 1
 
0.1%
120 8
1.1%
90 3
 
0.4%
70 1
 
0.1%
65 1
 
0.1%

averageRuntime
Real number (ℝ)

High correlation  Missing 

Distinct101
Distinct (%)15.5%
Missing57
Missing (%)8.1%
Infinite0
Infinite (%)0.0%
Mean42.560676
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:44.918406image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q122
median40
Q353.5
95-th percentile102.5
Maximum300
Range299
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation35.269432
Coefficient of variation (CV)0.82868591
Kurtosis13.021811
Mean42.560676
Median Absolute Deviation (MAD)16
Skewness2.9742766
Sum27707
Variance1243.9329
MonotonicityNot monotonic
2025-02-10T14:27:45.115553image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 40
 
5.6%
45 40
 
5.6%
60 39
 
5.5%
43 23
 
3.2%
25 23
 
3.2%
10 22
 
3.1%
15 21
 
3.0%
20 16
 
2.3%
12 14
 
2.0%
24 14
 
2.0%
Other values (91) 399
56.4%
(Missing) 57
 
8.1%
ValueCountFrequency (%)
1 2
 
0.3%
2 6
 
0.8%
3 5
 
0.7%
4 3
 
0.4%
5 7
 
1.0%
6 6
 
0.8%
7 6
 
0.8%
8 6
 
0.8%
9 4
 
0.6%
10 22
3.1%
ValueCountFrequency (%)
300 1
 
0.1%
242 1
 
0.1%
240 3
0.4%
219 1
 
0.1%
194 1
 
0.1%
184 1
 
0.1%
180 5
0.7%
177 1
 
0.1%
164 1
 
0.1%
163 1
 
0.1%
Distinct470
Distinct (%)66.4%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
Minimum1944-01-20 00:00:00
Maximum2024-11-25 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-10T14:27:45.285312image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:45.466445image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

ended
Date

Missing 

Distinct81
Distinct (%)45.8%
Missing531
Missing (%)75.0%
Memory size5.7 KiB
Minimum2024-01-01 00:00:00
Maximum2024-11-15 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-10T14:27:45.679502image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:45.888347image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

officialSite
URL

Missing 

Distinct625
Distinct (%)99.5%
Missing80
Missing (%)11.3%
Memory size70.1 KiB
https://abcnews.go.com/Live
 
4
https://www.ivi.ru/watch/nezhnost
 
1
https://www.youtube.com/playlist?list=PLs9aWCCF6Oy6CnOuLsq3GuDsb-9lZFrEf
 
1
https://www.svtplay.se/carina-bergfeldt
 
1
https://tv.nrk.no/serie/nytt-paa-nytt
 
1
Other values (620)
620 
(Missing)
80 
ValueCountFrequency (%)
https://abcnews.go.com/Live 4
 
0.6%
https://www.ivi.ru/watch/nezhnost 1
 
0.1%
https://www.youtube.com/playlist?list=PLs9aWCCF6Oy6CnOuLsq3GuDsb-9lZFrEf 1
 
0.1%
https://www.svtplay.se/carina-bergfeldt 1
 
0.1%
https://tv.nrk.no/serie/nytt-paa-nytt 1
 
0.1%
https://www.cbsnews.com/uplift/ 1
 
0.1%
https://www.peacocktv.com/stream-tv/the-traitors 1
 
0.1%
http://simonscat.com 1
 
0.1%
https://www.youtube.com/channel/UCHL9bfHTxCMi-7vfxQ-AYtg 1
 
0.1%
https://m.youtube.com/playlist?list=PL2Hx2rn1E3W5U-D0uLp8znb0RqKyXlC9L 1
 
0.1%
Other values (615) 615
86.9%
(Missing) 80
 
11.3%
ValueCountFrequency (%)
https 590
83.3%
http 38
 
5.4%
(Missing) 80
 
11.3%
ValueCountFrequency (%)
www.youtube.com 55
 
7.8%
v.qq.com 51
 
7.2%
www.bbc.co.uk 36
 
5.1%
www.netflix.com 33
 
4.7%
www.svtplay.se 17
 
2.4%
www.primevideo.com 17
 
2.4%
v.youku.com 15
 
2.1%
vk.com 15
 
2.1%
tv.nrk.no 13
 
1.8%
www.disneyplus.com 12
 
1.7%
Other values (199) 364
51.4%
(Missing) 80
 
11.3%
ValueCountFrequency (%)
/playlist 25
 
3.5%
/ 25
 
3.5%
6
 
0.8%
/Live 4
 
0.6%
/watch 3
 
0.4%
/x/search/ 3
 
0.4%
/serier/paradise-hotel 2
 
0.3%
/programmes/p01djw5m 1
 
0.1%
/show/revenge-our-dad-the-nazi-killer 1
 
0.1%
/show/muster-dogs 1
 
0.1%
Other values (557) 557
78.7%
(Missing) 80
 
11.3%
ValueCountFrequency (%)
556
78.5%
spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle 7
 
1.0%
lang=en_us 7
 
1.0%
spm=a2hbt.13141534.left-title-content-wrap.5~A 2
 
0.3%
list=PLShD8ZZW7qjmr-4yP8PpmnMhIjYv163fB 1
 
0.1%
spm_id_from=333.337.0.0 1
 
0.1%
s=acbfc1fe6bf948f7a3f7 1
 
0.1%
v=KsjjpB-EKdE&list=PLV8Q_exbQpnah3PkCNG8ao4sbWxqFdjSY 1
 
0.1%
view=50&sort=dd&shelf_id=5 1
 
0.1%
list=PLGwZKkKxJCidbu9qsXqjbvuLrbaayULav&si=rvA0JETf56jbjA3p 1
 
0.1%
Other values (50) 50
 
7.1%
(Missing) 80
 
11.3%
ValueCountFrequency (%)
626
88.4%
!/ 1
 
0.1%
detail 1
 
0.1%
(Missing) 80
 
11.3%

schedule_time
Categorical

Imbalance 

Distinct47
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size40.6 KiB
480 
10:00
 
35
12:00
 
32
20:00
 
20
00:00
 
15
Other values (42)
126 

Length

Max length5
Median length0
Mean length1.6101695
Min length0

Characters and Unicode

Total characters1140
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)3.8%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
480
67.8%
10:00 35
 
4.9%
12:00 32
 
4.5%
20:00 20
 
2.8%
00:00 15
 
2.1%
06:00 14
 
2.0%
18:00 14
 
2.0%
21:00 13
 
1.8%
02:00 11
 
1.6%
19:00 8
 
1.1%
Other values (37) 66
 
9.3%

Length

2025-02-10T14:27:46.089319image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10:00 35
15.4%
12:00 32
14.0%
20:00 20
 
8.8%
00:00 15
 
6.6%
06:00 14
 
6.1%
18:00 14
 
6.1%
21:00 13
 
5.7%
02:00 11
 
4.8%
17:00 8
 
3.5%
19:00 8
 
3.5%
Other values (36) 58
25.4%

Most occurring characters

ValueCountFrequency (%)
0 547
48.0%
: 228
20.0%
1 145
 
12.7%
2 103
 
9.0%
3 32
 
2.8%
9 19
 
1.7%
6 18
 
1.6%
8 17
 
1.5%
7 15
 
1.3%
5 11
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1140
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 547
48.0%
: 228
20.0%
1 145
 
12.7%
2 103
 
9.0%
3 32
 
2.8%
9 19
 
1.7%
6 18
 
1.6%
8 17
 
1.5%
7 15
 
1.3%
5 11
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1140
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 547
48.0%
: 228
20.0%
1 145
 
12.7%
2 103
 
9.0%
3 32
 
2.8%
9 19
 
1.7%
6 18
 
1.6%
8 17
 
1.5%
7 15
 
1.3%
5 11
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1140
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 547
48.0%
: 228
20.0%
1 145
 
12.7%
2 103
 
9.0%
3 32
 
2.8%
9 19
 
1.7%
6 18
 
1.6%
8 17
 
1.5%
7 15
 
1.3%
5 11
 
1.0%

schedule_days
Unsupported

Missing  Rejected  Unsupported 

Missing217
Missing (%)30.6%
Memory size55.6 KiB

rating
Real number (ℝ)

Missing 

Distinct43
Distinct (%)34.1%
Missing582
Missing (%)82.2%
Infinite0
Infinite (%)0.0%
Mean6.4888889
Minimum1
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:46.303588image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.15
Q16
median6.8
Q37.4
95-th percentile8
Maximum8.2
Range7.2
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.3969809
Coefficient of variation (CV)0.21528815
Kurtosis4.6906975
Mean6.4888889
Median Absolute Deviation (MAD)0.65
Skewness-1.9253958
Sum817.6
Variance1.9515556
MonotonicityNot monotonic
2025-02-10T14:27:47.121418image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
7.2 8
 
1.1%
7.4 7
 
1.0%
7.3 6
 
0.8%
7 6
 
0.8%
6.6 6
 
0.8%
8 6
 
0.8%
6.8 6
 
0.8%
7.8 5
 
0.7%
7.1 5
 
0.7%
6.3 5
 
0.7%
Other values (33) 66
 
9.3%
(Missing) 582
82.2%
ValueCountFrequency (%)
1 2
0.3%
1.3 1
0.1%
2.1 1
0.1%
2.2 1
0.1%
4.1 2
0.3%
4.3 1
0.1%
4.4 1
0.1%
4.6 1
0.1%
4.7 1
0.1%
4.8 1
0.1%
ValueCountFrequency (%)
8.2 1
 
0.1%
8.1 1
 
0.1%
8 6
0.8%
7.9 3
0.4%
7.8 5
0.7%
7.7 4
0.6%
7.6 4
0.6%
7.5 3
0.4%
7.4 7
1.0%
7.3 6
0.8%

weight
Real number (ℝ)

High correlation  Zeros 

Distinct99
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.526836
Minimum0
Maximum100
Zeros12
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:47.989682image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.35
Q18
median32
Q361
95-th percentile94
Maximum100
Range100
Interquartile range (IQR)53

Descriptive statistics

Standard deviation30.863538
Coefficient of variation (CV)0.82243912
Kurtosis-0.98514753
Mean37.526836
Median Absolute Deviation (MAD)24
Skewness0.57198329
Sum26569
Variance952.55798
MonotonicityNot monotonic
2025-02-10T14:27:48.256981image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 38
 
5.4%
7 36
 
5.1%
6 27
 
3.8%
3 25
 
3.5%
4 23
 
3.2%
23 21
 
3.0%
13 19
 
2.7%
11 16
 
2.3%
18 14
 
2.0%
1 14
 
2.0%
Other values (89) 475
67.1%
ValueCountFrequency (%)
0 12
 
1.7%
1 14
 
2.0%
2 10
 
1.4%
3 25
3.5%
4 23
3.2%
5 5
 
0.7%
6 27
3.8%
7 36
5.1%
8 38
5.4%
9 4
 
0.6%
ValueCountFrequency (%)
100 1
 
0.1%
99 7
1.0%
98 8
1.1%
97 5
0.7%
96 7
1.0%
95 7
1.0%
94 6
0.8%
93 6
0.8%
92 6
0.8%
91 2
 
0.3%

summary
Text

Missing 

Distinct612
Distinct (%)100.0%
Missing96
Missing (%)13.6%
Memory size327.3 KiB
2025-02-10T14:27:48.620065image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Length

Max length1931
Median length515
Mean length351.35621
Min length39

Characters and Unicode

Total characters215030
Distinct characters301
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique612 ?
Unique (%)100.0%

Sample

1st row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
2nd row<p>Lulin wasn't expecting to develop alien powers, or intergalactic invaders to crash her school science comp, but hey, Year 6 is full of surprises!</p>
3rd row<p>Ten thousand years ago, Muyun's fairy King was secretly accounted for by holding a Zhuxian figure, and after a long sleep, he awakened in the famous "Muyun waste" of the southern Yun Empire in the Land of Heaven. When Muyun first woke up, he was deliberately bothered by the student Miaoxianyu. Muyun easily completed the Miaoxianyu trap, and he gave more and more alchemy skills by analogy, so the Alchemy masters outside the door could not ask for appreciation. Endless back home, Mu Yun learns that he is about to marry Nona Qin Qin Mengyao. Qin Mengyao was cold and toxic, but could not live until he was 20 years old. The marriage was only for the sake of pastoralists and family of Qin. However, under Mu Linchen's enticement, Mu Yun approves the family's issue on the condition of alchemy.</p><p><br /> </p>
4th row<p>The former mighty Gods of the heavens, after ten thousand lifetimes of reincarnation tragically destroyed! The cruel curse, the hatred of ten thousand lives, Tan Yun determined, no longer sink! The most important thing is that you have to be able to get to the top of the world, step by step, stepping on the corpses of your enemies! To kill against the sky, across all the worlds, only I am the supreme!</p>
5th row<p>Of all the races in the world only 3 stand at the top. Each race possesses a master of the martial arts, a Golden Martial God. The balance of power appears to be shifting after Wang Fan's brother is killed triggering a chain of events that will begin to turn the world upside down. Disguising himself as the Silver Tiger King, Wang Fan becomes a symbol of power and the hope of the human race.<br />Some days Wang Fan is a boy genius that tries to blend in as a smart but helpless student. Other days he becomes a powerful tiger. Every race has their eyes on the Silver Tiger King as he continues to surpass every precedent and excel far beyond his peers all while under the guise of an unassuming student.</p>
ValueCountFrequency (%)
the 2180
 
6.2%
and 1266
 
3.6%
of 1053
 
3.0%
a 958
 
2.7%
to 896
 
2.5%
in 671
 
1.9%
is 416
 
1.2%
with 334
 
0.9%
on 274
 
0.8%
his 274
 
0.8%
Other values (8401) 26839
76.3%
2025-02-10T14:27:49.157679image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34501
16.0%
e 20605
 
9.6%
t 13782
 
6.4%
a 13154
 
6.1%
i 12370
 
5.8%
n 12171
 
5.7%
o 12067
 
5.6%
s 11213
 
5.2%
r 10384
 
4.8%
h 8707
 
4.0%
Other values (291) 66076
30.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 215030
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
34501
16.0%
e 20605
 
9.6%
t 13782
 
6.4%
a 13154
 
6.1%
i 12370
 
5.8%
n 12171
 
5.7%
o 12067
 
5.6%
s 11213
 
5.2%
r 10384
 
4.8%
h 8707
 
4.0%
Other values (291) 66076
30.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 215030
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
34501
16.0%
e 20605
 
9.6%
t 13782
 
6.4%
a 13154
 
6.1%
i 12370
 
5.8%
n 12171
 
5.7%
o 12067
 
5.6%
s 11213
 
5.2%
r 10384
 
4.8%
h 8707
 
4.0%
Other values (291) 66076
30.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 215030
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
34501
16.0%
e 20605
 
9.6%
t 13782
 
6.4%
a 13154
 
6.1%
i 12370
 
5.8%
n 12171
 
5.7%
o 12067
 
5.6%
s 11213
 
5.2%
r 10384
 
4.8%
h 8707
 
4.0%
Other values (291) 66076
30.7%

webChannel_name
Text

Missing 

Distinct147
Distinct (%)21.4%
Missing20
Missing (%)2.8%
Memory size46.0 KiB
2025-02-10T14:27:49.428039image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Length

Max length24
Median length22
Mean length8.1584302
Min length3

Characters and Unicode

Total characters5613
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)10.2%

Sample

1st rowИви
2nd rowOkko
3rd rowOkko
4th rowWink
5th rowKION
ValueCountFrequency (%)
youtube 101
 
10.0%
qq 55
 
5.4%
tencent 55
 
5.4%
tv 44
 
4.3%
netflix 35
 
3.5%
bbc 35
 
3.5%
iplayer 35
 
3.5%
play 35
 
3.5%
youku 28
 
2.8%
video 25
 
2.5%
Other values (179) 565
55.8%
2025-02-10T14:27:49.836113image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 511
 
9.1%
i 329
 
5.9%
325
 
5.8%
u 314
 
5.6%
o 293
 
5.2%
T 272
 
4.8%
n 238
 
4.2%
a 237
 
4.2%
l 202
 
3.6%
t 196
 
3.5%
Other values (73) 2696
48.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5613
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 511
 
9.1%
i 329
 
5.9%
325
 
5.8%
u 314
 
5.6%
o 293
 
5.2%
T 272
 
4.8%
n 238
 
4.2%
a 237
 
4.2%
l 202
 
3.6%
t 196
 
3.5%
Other values (73) 2696
48.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5613
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 511
 
9.1%
i 329
 
5.9%
325
 
5.8%
u 314
 
5.6%
o 293
 
5.2%
T 272
 
4.8%
n 238
 
4.2%
a 237
 
4.2%
l 202
 
3.6%
t 196
 
3.5%
Other values (73) 2696
48.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5613
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 511
 
9.1%
i 329
 
5.9%
325
 
5.8%
u 314
 
5.6%
o 293
 
5.2%
T 272
 
4.8%
n 238
 
4.2%
a 237
 
4.2%
l 202
 
3.6%
t 196
 
3.5%
Other values (73) 2696
48.0%

webChannel_site
URL

Missing 

Distinct90
Distinct (%)17.3%
Missing188
Missing (%)26.6%
Memory size47.2 KiB
https://www.youtube.com
101 
https://v.qq.com/
55 
https://www.netflix.com/
35 
https://www.bbc.co.uk/iplayer
35 
https://www.primevideo.com
 
24
Other values (85)
270 
(Missing)
188 
ValueCountFrequency (%)
https://www.youtube.com 101
14.3%
https://v.qq.com/ 55
 
7.8%
https://www.netflix.com/ 35
 
4.9%
https://www.bbc.co.uk/iplayer 35
 
4.9%
https://www.primevideo.com 24
 
3.4%
https://www.iq.com/ 23
 
3.2%
https://www.svtplay.se/ 18
 
2.5%
https://www.peacocktv.com/ 14
 
2.0%
https://tv.nrk.no 13
 
1.8%
https://www.disneyplus.com/ 12
 
1.7%
Other values (80) 190
26.8%
(Missing) 188
26.6%
ValueCountFrequency (%)
https 514
72.6%
http 6
 
0.8%
(Missing) 188
 
26.6%
ValueCountFrequency (%)
www.youtube.com 101
14.3%
v.qq.com 55
 
7.8%
www.netflix.com 35
 
4.9%
www.bbc.co.uk 35
 
4.9%
www.primevideo.com 24
 
3.4%
www.iq.com 23
 
3.2%
www.svtplay.se 18
 
2.5%
www.peacocktv.com 14
 
2.0%
tv.nrk.no 13
 
1.8%
www.disneyplus.com 12
 
1.7%
Other values (80) 190
26.8%
(Missing) 188
26.6%
ValueCountFrequency (%)
/ 290
41.0%
153
21.6%
/iplayer 35
 
4.9%
/video/@vkvideo 7
 
1.0%
/en 5
 
0.7%
/Live 4
 
0.6%
/onboarding 4
 
0.6%
/adlp/freevee-about 3
 
0.4%
/network/ 2
 
0.3%
/home 2
 
0.3%
Other values (13) 15
 
2.1%
(Missing) 188
26.6%
ValueCountFrequency (%)
512
72.3%
hpt=header_edition-picker 6
 
0.8%
utm_source=google&utm_campaign=gads_search_brand&utm_medium=cpc&utm_term=pure%20flix&hsa_ver=3&hsa_grp=68693273966&hsa_acc=9355037628&hsa_ad=676826129706&hsa_src=g&hsa_tgt=kwd-325450860434&hsa_kw=pure%20f 1
 
0.1%
ref=d6k_applink_bb_dls&dplnkId=cf2c8abd-2308-47e3-947b-b9f7e981c117 1
 
0.1%
(Missing) 188
 
26.6%
ValueCountFrequency (%)
520
73.4%
(Missing) 188
 
26.6%

dvd_country
Unsupported

Missing  Rejected  Unsupported 

Missing705
Missing (%)99.6%
Memory size22.9 KiB

externals_tvrage
Real number (ℝ)

High correlation  Missing 

Distinct23
Distinct (%)100.0%
Missing685
Missing (%)96.8%
Infinite0
Infinite (%)0.0%
Mean17498.696
Minimum712
Maximum47170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:49.997808image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum712
5-th percentile1999.7
Q15036
median15090
Q331222
95-th percentile35682.6
Maximum47170
Range46458
Interquartile range (IQR)26186

Descriptive statistics

Standard deviation14066.247
Coefficient of variation (CV)0.80384543
Kurtosis-1.1312229
Mean17498.696
Median Absolute Deviation (MAD)11672
Skewness0.45531338
Sum402470
Variance1.9785929 × 108
MonotonicityNot monotonic
2025-02-10T14:27:50.140987image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3418 1
 
0.1%
15090 1
 
0.1%
32413 1
 
0.1%
10092 1
 
0.1%
35853 1
 
0.1%
5199 1
 
0.1%
3005 1
 
0.1%
4920 1
 
0.1%
47170 1
 
0.1%
31493 1
 
0.1%
Other values (13) 13
 
1.8%
(Missing) 685
96.8%
ValueCountFrequency (%)
712 1
0.1%
1888 1
0.1%
3005 1
0.1%
3256 1
0.1%
3418 1
0.1%
4920 1
0.1%
5152 1
0.1%
5199 1
0.1%
6659 1
0.1%
8531 1
0.1%
ValueCountFrequency (%)
47170 1
0.1%
35853 1
0.1%
34149 1
0.1%
33858 1
0.1%
32413 1
0.1%
31493 1
0.1%
30951 1
0.1%
26056 1
0.1%
25100 1
0.1%
19056 1
0.1%

externals_thetvdb
Real number (ℝ)

High correlation  Missing 

Distinct510
Distinct (%)100.0%
Missing198
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean390421.6
Minimum70366
Maximum457021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:50.293248image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum70366
5-th percentile242895.5
Q1374678.5
median423039.5
Q3442143.5
95-th percentile445129.7
Maximum457021
Range386655
Interquartile range (IQR)67465

Descriptive statistics

Standard deviation81308.181
Coefficient of variation (CV)0.20825739
Kurtosis5.5107192
Mean390421.6
Median Absolute Deviation (MAD)20814.5
Skewness-2.3385838
Sum1.9911502 × 108
Variance6.6110203 × 109
MonotonicityNot monotonic
2025-02-10T14:27:50.477869image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
389662 1
 
0.1%
362235 1
 
0.1%
145431 1
 
0.1%
444655 1
 
0.1%
428163 1
 
0.1%
135211 1
 
0.1%
395604 1
 
0.1%
410849 1
 
0.1%
449126 1
 
0.1%
441368 1
 
0.1%
Other values (500) 500
70.6%
(Missing) 198
 
28.0%
ValueCountFrequency (%)
70366 1
0.1%
71178 1
0.1%
71753 1
0.1%
71756 1
0.1%
72716 1
0.1%
76355 1
0.1%
76719 1
0.1%
76779 1
0.1%
78006 1
0.1%
78419 1
0.1%
ValueCountFrequency (%)
457021 1
0.1%
454395 1
0.1%
451493 1
0.1%
449126 1
0.1%
448382 1
0.1%
447745 1
0.1%
447439 1
0.1%
447332 1
0.1%
447062 1
0.1%
446981 1
0.1%

externals_imdb
Text

Missing 

Distinct364
Distinct (%)100.0%
Missing344
Missing (%)48.6%
Memory size34.6 KiB
2025-02-10T14:27:50.765838image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.75
Min length9

Characters and Unicode

Total characters3549
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique364 ?
Unique (%)100.0%

Sample

1st rowtt20603062
2nd rowtt15816496
3rd rowtt19756810
4th rowtt27432264
5th rowtt27801903
ValueCountFrequency (%)
tt30249032 1
 
0.3%
tt0058796 1
 
0.3%
tt15816496 1
 
0.3%
tt19756810 1
 
0.3%
tt27432264 1
 
0.3%
tt27801903 1
 
0.3%
tt0088512 1
 
0.3%
tt0338653 1
 
0.3%
tt11847842 1
 
0.3%
tt7057262 1
 
0.3%
Other values (354) 354
97.3%
2025-02-10T14:27:51.967167image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 728
20.5%
2 406
11.4%
1 323
9.1%
0 320
9.0%
4 284
 
8.0%
8 280
 
7.9%
6 275
 
7.7%
3 270
 
7.6%
5 228
 
6.4%
9 222
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3549
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 728
20.5%
2 406
11.4%
1 323
9.1%
0 320
9.0%
4 284
 
8.0%
8 280
 
7.9%
6 275
 
7.7%
3 270
 
7.6%
5 228
 
6.4%
9 222
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3549
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 728
20.5%
2 406
11.4%
1 323
9.1%
0 320
9.0%
4 284
 
8.0%
8 280
 
7.9%
6 275
 
7.7%
3 270
 
7.6%
5 228
 
6.4%
9 222
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3549
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 728
20.5%
2 406
11.4%
1 323
9.1%
0 320
9.0%
4 284
 
8.0%
8 280
 
7.9%
6 275
 
7.7%
3 270
 
7.6%
5 228
 
6.4%
9 222
 
6.3%

updated
Real number (ℝ)

Unique 

Distinct708
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7230735 × 109
Minimum1.6991738 × 109
Maximum1.7390499 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.7 KiB
2025-02-10T14:27:52.227260image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Quantile statistics

Minimum1.6991738 × 109
5-th percentile1.7049509 × 109
Q11.7089776 × 109
median1.7248104 × 109
Q31.7366427 × 109
95-th percentile1.7389195 × 109
Maximum1.7390499 × 109
Range39876172
Interquartile range (IQR)27665127

Descriptive statistics

Standard deviation13227526
Coefficient of variation (CV)0.0076767043
Kurtosis-1.6384882
Mean1.7230735 × 109
Median Absolute Deviation (MAD)12908616
Skewness-0.13977696
Sum1.219936 × 1012
Variance1.7496743 × 1014
MonotonicityNot monotonic
2025-02-10T14:27:52.423996image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1704215354 1
 
0.1%
1716477793 1
 
0.1%
1705082793 1
 
0.1%
1739049934 1
 
0.1%
1720023117 1
 
0.1%
1738933330 1
 
0.1%
1706695649 1
 
0.1%
1738908292 1
 
0.1%
1707291460 1
 
0.1%
1737984176 1
 
0.1%
Other values (698) 698
98.6%
ValueCountFrequency (%)
1699173762 1
0.1%
1699196321 1
0.1%
1700067953 1
0.1%
1701776723 1
0.1%
1703096478 1
0.1%
1703404987 1
0.1%
1703852377 1
0.1%
1703934794 1
0.1%
1704019326 1
0.1%
1704104449 1
0.1%
ValueCountFrequency (%)
1739049934 1
0.1%
1739049891 1
0.1%
1739049038 1
0.1%
1739043766 1
0.1%
1739042508 1
0.1%
1739040763 1
0.1%
1739039426 1
0.1%
1739039394 1
0.1%
1739036311 1
0.1%
1739033647 1
0.1%

Interactions

2025-02-10T14:27:39.667763image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:30.287088image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:31.742112image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:33.015361image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:34.256047image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:35.547215image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:36.749632image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:37.949673image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:40.215766image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:30.424906image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:31.904485image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:33.161518image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:34.405920image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:35.711925image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:36.886857image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:38.118576image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:40.533746image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:30.662141image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:32.044819image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:33.307703image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:34.680242image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:35.860228image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:37.022711image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:38.286114image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:40.714928image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:30.828727image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:32.211239image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:33.478446image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:34.817477image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:36.012117image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:37.160980image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:38.451067image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:40.880730image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:31.030537image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:32.344369image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:33.663064image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:34.957025image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:36.148187image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:37.301898image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:38.617158image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:41.079304image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:31.238887image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:32.527812image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:33.819044image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:35.087859image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:36.292795image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:37.454885image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:38.783970image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:41.248025image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:31.430296image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:32.696546image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:33.966364image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:35.240497image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:36.432093image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:37.603540image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:38.948105image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:41.412174image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:31.596012image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:32.835793image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:34.111463image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:35.392997image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:36.593472image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:37.752894image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
2025-02-10T14:27:39.223772image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/

Correlations

2025-02-10T14:27:52.611793image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
averageRuntimeexternals_thetvdbexternals_tvrageidlanguageratingruntimeschedule_timestatustypeupdatedweight
averageRuntime1.000-0.0980.069-0.0620.0000.0230.9930.3460.0980.2910.0370.102
externals_thetvdb-0.0981.0000.9360.8320.215-0.248-0.1750.4080.2180.195-0.403-0.428
externals_tvrage0.0690.9361.0000.2140.493-0.1790.2050.0000.0000.3160.049-0.297
id-0.0620.8320.2141.0000.085-0.236-0.0030.2270.1880.154-0.288-0.592
language0.0000.2150.4930.0851.0000.0000.1620.1790.3570.2060.1690.085
rating0.023-0.248-0.179-0.2360.0001.0000.0880.0000.1680.1050.2620.249
runtime0.993-0.1750.205-0.0030.1620.0881.0000.3910.0000.3050.041-0.005
schedule_time0.3460.4080.0000.2270.1790.0000.3911.0000.1820.2180.0000.125
status0.0980.2180.0000.1880.3570.1680.0000.1821.0000.3790.3140.182
type0.2910.1950.3160.1540.2060.1050.3050.2180.3791.0000.1300.097
updated0.037-0.4030.049-0.2880.1690.2620.0410.0000.3140.1301.0000.368
weight0.102-0.428-0.297-0.5920.0850.249-0.0050.1250.1820.0970.3681.000

Missing values

2025-02-10T14:27:41.835058image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-10T14:27:42.365244image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-10T14:27:42.650667image/svg+xmlMatplotlib v3.5.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idurlnametypelanguagegenresstatusruntimeaverageRuntimepremieredendedofficialSiteschedule_timeschedule_daysratingweightsummarywebChannel_namewebChannel_sitedvd_countryexternals_tvrageexternals_thetvdbexternals_imdbupdated
051908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost<NA>NaN11NoneИвиhttps://www.ivi.ru/NoneNaNNaNNone1704215354
159205https://www.tvmaze.com/shows/59205/predposlednaa-instanciaПредпоследняя инстанцияScriptedRussian[Drama, Comedy, Supernatural]EndedNaN26.02022-01-012024-01-08https://okko.tv/serial/predposlednjaja-instancija[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN29NoneOkkoNoneNoneNaNNaNNone1704783571
259484https://www.tvmaze.com/shows/59484/manunaМанюняScriptedRussian[Comedy, Adventure, Children]RunningNaN20.02021-12-15Nonehttps://okko.tv/serial/manjunja[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]6.331NoneOkkoNoneNoneNaN413379.0None1703404987
372871https://www.tvmaze.com/shows/72871/nedetskoe-kinoНедетское киноScriptedNone[Comedy, Fantasy]RunningNaNNaN2024-01-01Nonehttps://wink.ru/series/ne-detskoe-kino-year-2023?ysclid=lpbaiai0cw654763598<NA>NaN3NoneWinkNoneNoneNaNNaNNone1704019326
473221https://www.tvmaze.com/shows/73221/uspesnyjУспешныйScriptedRussian[Comedy]RunningNaNNaN2024-01-01Nonehttps://kion.ru/video/serial/822094895/season/822095042/episode/822094715<NA>NaN6<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>KIONhttps://kion.ru/NoneNaNNaNNone1735808422
573590https://www.tvmaze.com/shows/73590/kak-druza-zahara-zeniliКак друзья Захара женилиScriptedNone[Comedy]EndedNaN26.02024-01-012024-02-06None<NA>NaN16NoneOkkoNoneNoneNaNNaNNone1707351592
673893https://www.tvmaze.com/shows/73893/imperatricyИмператрицыDocumentaryNone[Drama, History]EndedNaN39.02024-01-012024-01-01https://premier.one/show/imperatritsy-mini-serial<NA>NaN3NonePremierhttps://premier.one/NoneNaNNaNNone1705416247
773780https://www.tvmaze.com/shows/73780/planet-lulinPlanet LulinScriptedEnglish[Children, Fantasy, Science-Fiction]To Be DeterminedNaN22.02024-01-01Nonehttps://iview.abc.net.au/show/planet-lulin<NA>NaN27<p>Lulin wasn't expecting to develop alien powers, or intergalactic invaders to crash her school science comp, but hey, Year 6 is full of surprises!</p>ABC iviewhttps://iview.abc.net.au/NoneNaN444536.0None1705107854
855019https://www.tvmaze.com/shows/55019/supreme-god-emperorSupreme God EmperorAnimationChinese[Adventure, Anime, Fantasy]Running10.010.02020-05-18Nonehttps://v.qq.com/x/search/?q=无上神帝&stag=&smartbox_ab=10:00[Monday, Friday]NaN49<p>Ten thousand years ago, Muyun's fairy King was secretly accounted for by holding a Zhuxian figure, and after a long sleep, he awakened in the famous "Muyun waste" of the southern Yun Empire in the Land of Heaven. When Muyun first woke up, he was deliberately bothered by the student Miaoxianyu. Muyun easily completed the Miaoxianyu trap, and he gave more and more alchemy skills by analogy, so the Alchemy masters outside the door could not ask for appreciation. Endless back home, Mu Yun learns that he is about to marry Nona Qin Qin Mengyao. Qin Mengyao was cold and toxic, but could not live until he was 20 years old. The marriage was only for the sake of pastoralists and family of Qin. However, under Mu Linchen's enticement, Mu Yun approves the family's issue on the condition of alchemy.</p><p><br /> </p>Tencent QQhttps://v.qq.com/NoneNaN388383.0tt206030621732535501
962143https://www.tvmaze.com/shows/62143/against-the-sky-supremeAgainst the Sky SupremeAnimationChinese[Action, Adventure, Anime, Fantasy]RunningNaN7.02021-07-09Nonehttps://v.qq.com/x/cover/mzc00200azkttu2.html10:00[Monday, Friday]7.882<p>The former mighty Gods of the heavens, after ten thousand lifetimes of reincarnation tragically destroyed! The cruel curse, the hatred of ten thousand lives, Tan Yun determined, no longer sink! The most important thing is that you have to be able to get to the top of the world, step by step, stepping on the corpses of your enemies! To kill against the sky, across all the worlds, only I am the supreme!</p>Tencent QQhttps://v.qq.com/NoneNaN406729.0tt158164961738619115
idurlnametypelanguagegenresstatusruntimeaverageRuntimepremieredendedofficialSiteschedule_timeschedule_daysratingweightsummarywebChannel_namewebChannel_sitedvd_countryexternals_tvrageexternals_thetvdbexternals_imdbupdated
69834499https://www.tvmaze.com/shows/34499/off-gun-fun-nightOff Gun Fun NightTalk ShowThai[Drama, Comedy]EndedNaN23.02017-11-122024-01-31https://tv.line.me/offgunfunnight?lang=th_TH<NA>NaN34<p>A monthly talk show where Off and Gun host a special guest and a lot of fun and laughs ensue. Airs every 12th of the month.</p>LINE TVhttps://www.linetv.tw/NoneNaN347036.0None1706727249
69940868https://www.tvmaze.com/shows/40868/gods-school-the-olympian-godsGods' School: The Olympian GodsAnimationEnglish<NA>Running15.013.02019-01-31Nonehttps://www.youtube.com/channel/UC4E060sRvClagErOdYZZjVA[Saturday]NaN21<p>Mount Olympus is the divine sanctuary created by the Titans for the young gods and goddesses, Among the young immortals, one young goddess, Eris, is a black sheep. She has an horrible reputation, she doesn't fit the high standards of Mount Olympus and she is is being avoid like the plague. But her meeting with a mortal is going to change her divine destiny.</p>YouTubehttps://www.youtube.comNoneNaN355452.0tt89298261706859211
70053613https://www.tvmaze.com/shows/53613/marvel-studios-assembledMarvel Studios: AssembledDocumentaryEnglish<NA>RunningNaN57.02021-03-12Nonehttps://disneyplus.com/series/marvel-studios-assembled/3RUQKboZV3FF<NA>7.995<p><b>Marvel Studios: Assembled</b> is a comprehensive documentary series streaming on Disney+ that chronicles the creation of Marvel Studios' thrilling new shows and theatrical releases. Journey behind-the-scenes of productions such as <i>WandaVision</i>, <i>The Falcon and the Winter Soldier</i>, and <i>Loki</i> via exclusive on-set footage. <i>Assembled</i> is an immersive, and in-depth examination of the next phase of the Marvel Cinematic Universe.</p>Disney+https://www.disneyplus.com/NoneNaN396948.0tt140942061734639089
70166629https://www.tvmaze.com/shows/66629/love-never-lies-polskaLove Never Lies: PolskaRealityPolish[Romance]To Be DeterminedNaN49.02023-01-25Nonehttps://www.netflix.com/title/81582706<NA>NaN52<p>Six couples test their trust with an eye-scanning lie detector in this reality series where deception costs money, and the truth comes with a prize.</p>Netflixhttps://www.netflix.com/NoneNaN430211.0tt253775961729271534
70273378https://www.tvmaze.com/shows/73378/choirChoirDocumentaryEnglish[Family, Music]RunningNaN46.02024-01-31Nonehttps://www.disneyplus.com/series/choir/2ZObNbv5pKlj<NA>NaN27<p><b>Choir</b> follows the kids of the Detroit Youth Choir as they prepare for the performance of a lifetime. Through their eyes, we experience the highs and lows of life growing up in Detroit, navigating the challenges of balancing family, school, and athletics, all while pursuing their dreams of taking their talents to the next level and performing on one of the world's biggest stages. Following their 2019 appearance on America's Got Talent, it's a pivotal time for the choir and its director, Anthony White, as he's faced with the combined challenges of replacing several key members, keeping the choir relevant in Detroit, and finding the next big opportunity that will put them back in the national spotlight.</p>Disney+https://www.disneyplus.com/NoneNaN443679.0tt280807211706780799
70373413https://www.tvmaze.com/shows/73413/baby-banditoBaby BanditoScriptedSpanish[Drama, Crime, Thriller]EndedNaN38.02024-01-312024-01-31https://www.netflix.com/title/81619198<NA>5.342<p>After skater Kevin and his crew pull off Chile's biggest heist, reckless love –and social media– threatens everyone's fortunes. Inspired by true events.</p>Netflixhttps://www.netflix.com/NoneNaN444012.0tt279977131706822844
70473714https://www.tvmaze.com/shows/73714/alexander-the-making-of-a-godAlexander: The Making of a GodDocumentaryEnglish[History]EndedNaN39.02024-01-312024-01-31https://www.netflix.com/title/81325194<NA>6.186<p>Combining expert interviews with gripping reenactments, this docudrama explores the life of Alexander the Great through his conquest of the Persian Empire.</p>Netflixhttps://www.netflix.com/NoneNaN444188.0tt274949991707151653
70574390https://www.tvmaze.com/shows/74390/fighting-for-loveFighting for LoveScriptedChinese[Action, Romance, War]EndedNaN45.02024-01-312024-02-21https://www.iqiyi.com/v_26mc92p2eag.html[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN13<p>The story follows Amai, a female general of the founding era of the Southern Xia dynasty, who discards her feminine attire and dons battle armor, enduring hardships to become a legendary female warrior. Amai (Zhang Tianai), the daughter of the Duke of Jingguo in Southern Xia, witnesses her entire family being killed by her childhood friend Chen Qi. Years later, Amai, now a young girl, disguises herself as a man and roams the martial world, seeking revenge against Chen Qi. Through a series of coincidences, Amai saves Shang Yizhi (Zhang Haowei), the son of the Grand Princess, and subsequently helps him escape from dangerous situations multiple times, intertwining their destinies. As war breaks out, Amai sheds her feminine attire and joins the military, becoming an infantry soldier. With her exceptional military talents, she achieves remarkable feats and rises to the rank of General Mai. Alongside this, she assists Shang Yizhi, who is hunted and faces difficulties, in finding his true self and accomplishing great deeds. On the battlefield, Amai repeatedly clashes with General Chang Yuqing (Wang Ruichang) from the enemy forces. Despite their confrontations, they unintentionally go through life-and-death situations together, developing a mutual understanding and respect. However, faced with the brutality of war, Amai willingly sets aside personal attachments and uses her youth and fervor to defend her army. Eventually, after the war's victory, Amai leaves the military, returns to her female identity, retreats from the world, and ultimately finds her own happiness.</p>iQIYIhttps://www.iq.com/NoneNaN439696.0None1708493403
70678088https://www.tvmaze.com/shows/78088/hot-ones-versusHot Ones VersusTalk ShowEnglish[Food]RunningNaN15.02024-01-31Nonehttps://www.youtube.com/playlist?list=PLAzrgbu8gEMKThlhJv0ftFDvsumn0f-HN<NA>NaN45<p>"Hot Ones" spin-off series where guests have two choices: Tell the truth, or suffer the wrath of the Last Dab. Whoever eats the most wings, loses.</p>YouTubehttps://www.youtube.comNoneNaNNaNtt313232461738724974
70775220https://www.tvmaze.com/shows/75220/sues-placesSue's PlacesTalk ShowEnglish[Sports]RunningNaNNaN2024-01-31Nonehttps://www.espn.com/watch/series/0b15b405-50b7-4e8b-a553-cfee4ef2a89d/sues-places[Wednesday]NaN8<p>UConn legend Sue Bird explores the rich history, traditions and seminal moments of men's and women's college basketball.</p>ESPN+NoneNoneNaNNaNNone1710010766